System for tracking and analyzing welding activity

ABSTRACT

A system and a method for tracking and analyzing welding activity. Dynamic spatial properties of a welding tool are sensed during a welding process producing a weld. The sensed dynamic spatial properties are tracked over time and the tracked dynamic spatial properties are captured as tracked data during the welding process. The tracked data is analyzed to determine performance characteristics of a welder performing the welding process and quality characteristics of a weld produced by the welding process. The performance characteristics and the quality characteristics may be subsequently reviewed.

This U.S. patent application claims priority to and the benefit of U.S.provisional patent application Ser. No. 61/158,578 which was filed onMar. 9, 2009, and which is incorporated herein by reference in itsentirety.

TECHNICAL FIELD

Certain embodiments of the present invention pertain to systems fortracking and analyzing welding activity, and more particularly, tosystems that capture weld data in real time (or near real time) foranalysis and review. Additionally, the embodiments of the presentinvention provide a system for marking portions of a welded article byindicating possible discontinuities or flaws within the weld joint.

BACKGROUND

In many applications, ascertaining the quality of weld joints iscritical to the use and operation of a machine or structureincorporating a welded article. In some instances, x-raying or othernondestructive testing is needed to identify potential flaws within oneor more welded joints. However, non-destructive testing can becumbersome to use, and typically lags the welding process until theinspector arrives to complete the testing. Additionally, it may not beeffective for use with all weld joint configurations. Moreover,non-destructive testing does not provide any information about how theweld was completed. In welding applications where identifying waste isvital to producing cost effective parts, non-destructive testingprovides no insight into problems like overfill.

Further limitations and disadvantages of conventional, traditional, andproposed approaches will become apparent to one of skill in the art,through comparison of such approaches with the subject matter of thepresent application as set forth in the remainder of the presentapplication with reference to the drawings.

SUMMARY

The embodiments of the present invention pertain to a system fortracking and analyzing welding activity. The system may be used inconjunction with a welding power supply and includes a sensor array andlogic processor-based technology that captures performance data (dynamicspatial properties) as the welder performs various welding activities.The system functions to evaluate the data via an analysis engine fordetermining weld quality in real time (or near real time). The systemalso functions to store and replay data for review at a time subsequentto the welding activity thereby allowing other users of the system toreview the performance activity of the welding process.

These and other novel features of the subject matter of the presentapplication, as well as details of illustrated embodiments thereof, willbe more fully understood from the following description and drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a perspective view of a welder using an embodiment of a systemfor tracking and analyzing welding activity;

FIG. 2 is a schematic representation of an embodiment of the system ofFIG. 1 for tracking and analyzing welding activity;

FIG. 3 is a schematic representation of an embodiment of the hardwareand software of the system of FIGS. 1-2 for tracking and analyzingwelding activity;

FIG. 4 is a flow diagram of an embodiment of the system of FIGS. 1-3 fortracking and analyzing welding activity;

FIG. 5 is a flowchart of an embodiment of a method for tracking andanalyzing welding activity using the system of FIGS. 1-4; and

FIG. 6 illustrates an example embodiment of a graph, displayed on adisplay, showing tracked welding tool pitch angle versus time withrespect to an upper pitch angle limit, a lower pitch angle limit, and anideal pitch angle.

DETAILED DESCRIPTION

FIG. 1 is a perspective view of a welder 10 using an embodiment of asystem 100 for tracking and analyzing welding activity while performinga welding process with a welding system 200. FIG. 2 is a schematicrepresentation of an embodiment of the system 100 of FIG. 1 for trackingand analyzing welding activity. FIG. 3 is a schematic representation ofan embodiment of the hardware 110, 130 and software 120 of the system100 of FIGS. 1-2 for tracking and analyzing welding activity. FIG. 4 isa flow diagram of an embodiment of the system 100 of FIGS. 1-3 fortracking and analyzing welding activity. FIG. 5 is a flowchart of anembodiment of a method 500 for tracking and analyzing welding activityusing the system 100 of FIGS. 1-4.

Referring again to the drawings wherein the showings are for purposes ofillustrating embodiments of the invention only and not for purposes oflimiting the same, FIG. 1 shows a system 100 for tracking and analyzingmanual processes requiring the dexterity of a human end user 10. Inparticular, system 100 functions to capture performance data related tothe use and handling of tools (e.g., welding tools). In one embodiment,the system 100 is used to track and analyze welding activity, which maybe a manual welding process in any of its forms including but notlimited to: arc welding, laser welding, brazing, soldering, oxyacetyleneand gas welding, and the like. For illustrative purposes, theembodiments of the present invention will be described in the context ofarc welding. However, persons of ordinary skill in the art willunderstand its application to other manual processes. In accordance withalternative embodiments of the present invention, the manual welder 10may be replaced with a robotic welder. As such, the performance of therobotic welder and resultant weld quality may be determined in a similarmanner.

In one embodiment, the system 100 tracks movement or motion (i.e.,position and orientation over time) of a welding tool 230, which may be,for example, an electrode holder or a welding torch. Accordingly, thesystem 100 is used in conjunction with a welding system 200 including awelding power supply 210, a welding torch 230, and welding cables 240,along with other welding equipment and accessories. As a welder 10, i.e.end user 10, performs welding activity in accordance with a weldingprocess, the system 100 functions to capture performance data from realworld welding activity as sensed by sensors 160, 165 (see FIG. 2) whichare discussed in more detail later herein.

In accordance with an embodiment of the present invention, the system100 for tracking and analyzing welding activity includes the capabilityto automatically sense dynamic spatial properties (e.g., positions,orientations, and movements) of a welding tool 230 during a manualwelding process producing a weld 16 (e.g., a weld joint). The system 100further includes the capability to automatically track the senseddynamic spatial properties of the welding tool 230 over time andautomatically capture (e.g., electronically capture) the tracked dynamicspatial properties of the welding tool 230 during the manual weldingprocess.

The system 100 also includes the capability to automatically analyze thetracked data to determine performance characteristics of a welder 10performing the manual welding process and quality characteristics of aweld 16 produced by the welding process. The system 100 allows for theperformance characteristics of the welder 10 and the qualitycharacteristics of the weld to be reviewed. The performancecharacteristics of a welder 10 may include, for example, a weld jointtrajectory, a travel speed of the welding tool 230, welding tool pitchand roll angles, an electrode distance to a center weld joint, anelectrode trajectory, and a weld time. The quality characteristics of aweld produced by the welding process may include, for example,discontinuities and flaws within certain regions of a weld produced bythe welding process.

The system 100 further allows a user (e.g., a welder 10) to locallyinteract with the system 100. In accordance with another embodiment ofthe present invention, the system 100 allows a remotely located user toremotely interact with the system 100. In either scenario, the system100 may automatically authorize access to a user of the system 100,assuming such authorization is warranted.

In accordance with an embodiment of the present invention, the system100 for tracking and analyzing welding activity includes a processorbased computing device 110 configured to track and analyze dynamicspatial properties (e.g., positions, orientations, and movements) of awelding tool 230 over time during a manual welding process producing aweld 16. The system 100 further includes at least one sensor array 160,165 operatively interfacing to the processor based computing device 110(wired or wirelessly) and configured to sense the dynamic spatialproperties of a welding tool 230 during a manual welding processproducing a weld 16. The system 100 also includes at least one userinterface operatively interfacing to the processor based computingdevice 110. The user interface may include a graphical user interface135 and/or a display device (e.g., a display 130 or a welding displayhelmet 180 where a display is integrated into a welding helmet asillustrated in FIG. 2). The system 100 may further include a networkinterface configured to interface the processor based computing device110 to a communication network 300 (e.g., the internet).

In accordance with an embodiment of the present invention, a method 500(see FIG. 5) for tracking and analyzing welding activity includes, instep 510, setting up a manual welding process, and, in step 520, sensingdynamic spatial properties (e.g., positions, orientations, andmovements) of a welding tool 230 during a manual welding processproducing a weld using at least one sensor (e.g., sensor arrays 160 and165). In step 530, the method includes tracking the sensed dynamicspatial properties over time during the manual welding process using areal time tracking module 121 (see FIG. 4). The method also includes, instep 540, capturing the tracked dynamic spatial properties as trackeddata during the manual welding process using a computer based (e.g.,electronic) memory device (e.g., a portion of the hardware 150 andsoftware 120 of the processor based computing device 110). The methodfurther includes, in step 550, analyzing the tracked data to determineperformance characteristics of a welder 10 performing the manual weldingprocess and/or quality characteristics of a weld produced by the weldingprocess using a computer based analysis engine 122. In step 560, atleast one of the performance characteristics and the qualitycharacteristics are reviewed using a display device (e.g., displaydevice 130). Alternatively, a visualization module or a testing modulemay be used in place of the display device 130, as are well known in theart.

The method 500 may initially include selecting welding set up parametersfor the welding process via a user interface 135 as part of step 510.The method may also include outputting the performance characteristicsof the welder 10 and/or the quality characteristics of a weld to aremote location and remotely viewing the performance characteristicsand/or the quality characteristics via a communication network 300 (seeFIG. 3).

The system 100 for tracking and analyzing welding activity compriseshardware and software components, in accordance with an embodiment ofthe present invention. In one embodiment, the system 100 incorporateselectronic hardware. More specifically, system 100 may be constructed,at least in part, from electronic hardware 150 (see FIG. 4) of theprocessor based computing device 110 operable to execute programmedalgorithms, also referred to herein as software 120 or a computerprogram product. The processor based computing device 110 may employ oneor more logic processors capable of being programmed, an example ofwhich may include one or more microprocessors. However, other types ofprogrammable circuitry may be used without departing from the intendedscope of coverage of the embodiments of the present invention. In oneembodiment, the processor based computing device 110 is operativelydisposed as a microcomputer in any of various configurations includingbut not limited to: a laptop computer, a desktop computer, a workstation, a server or the like. Alternatively, mini-computers or mainframe computers may serve as the platform for implementing the system100 for tracking and analyzing welding activity. Moreover, handheld ormobile processor based computing devices may be used to executeprogrammable code for tracking and analyzing performance data.

Other embodiments are contemplated wherein the system 100 isincorporated into the welding system 200. More specifically, thecomponents comprising the system 100 may be integrated into the weldingpower supply 210 and/or weld torch 230. For example, the processor basedcomputing device 110 may be received internal to the housing of thewelding power supply 210 and may share a common power supply with othersystems located therein. Additionally, sensors 160, 165, used to sensethe weld torch 230 dynamic spatial properties, may be integrated intothe weld torch handle.

The system 100 may communicate with and be used in conjunction withother similarly or dissimilarly constructed systems. Input to and outputfrom the system 100, termed I/O, may be facilitated by networkinghardware and software including wireless as well as hard wired (directlyconnected) network interface devices. Communication to and from thesystem 100 may be accomplished remotely as through a network 300 (seeFIG. 3), such as, for example, a wide area network (WAN) or theInternet, or through a local area network (LAN) via network hubs,repeaters, or by any means chosen with sound engineering judgment. Inthis manner, information may be transmitted between systems as is usefulfor analyzing, and/or re-constructing and displaying performance andquality data.

In one embodiment, remote communications are used to provide virtualinstruction by personnel, i.e. remote or offsite users, not located atthe welding site. Reconstruction of the welding process is accomplishedvia networking. Data representing a particular weld may be sent toanother similar or dissimilar system 100 capable of displaying the welddata (see FIG. 3). It should be noted that the transmitted data issufficiently detailed for allowing remote user(s) to analyze thewelder's performance and the resultant weld quality. Data sent to aremote system 100 may be used to generate a virtual welding environmentthereby recreating the welding process as viewed by offsite users asdiscussed later herein. Still, any way of communicating performance datato another entity remotely located from the welding site may be usedwithout departing from the intended scope of coverage of the embodimentsof the subject invention.

The processor based computing device 110 further includes supportcircuitry including electronic memory devices, along with otherperipheral support circuitry that facilitate operation of the one ormore logic processor(s), in accordance with an embodiment of the presentinvention. Additionally, the processor based computing device 110 mayinclude data storage, examples of which include hard disk drives,optical storage devices and/or flash memory for the storage andretrieval of data. Still any type of support circuitry may be used withthe one or more logic processors as chosen with sound engineeringjudgment. Accordingly, the processor based computing device 110 may beprogrammable and operable to execute coded instructions in a high or lowlevel programming language. It should be noted that any form ofprogramming or type of programming language may be used to codealgorithms as executed by the system 100.

With reference now to FIGS. 1-4, the system 100 is accessible by the enduser 10 via a display screen 130 operatively connected to the processorbased computing device 110. Software 120 installed onto the system 100directs the end user's 10 interaction with the system 100 by displayinginstructions and/or menu options on, for example, the display screen 130via one or more graphical user interfaces (GUI) 135. Interaction withthe system 100 includes functions relating to, for example: part set up(weld joint set up), welding activity analysis, weld activity playback,real time tracking, as well as administrative activity for managing thecaptured data. Still other functions may be chosen as are appropriatefor use with the embodiments of the present invention. System navigationscreens, i.e. menu screens, may be included to assist the end user 10 intraversing through the system functions. It is noted that as the system100 is used for training and analysis, security may be incorporated intothe GUI(s) 135 that allow restricted access to various groups of endusers 10. Password security, biometrics, work card arrangement or othersecurity measures may be used to ensure that system access is given onlyto authorized users as determined by an administrator or administrativeuser. It will be appreciated that the end user 10 may be the same or adifferent person than that of the administrative user.

In one embodiment, the system 100 functions to capture performance dataof the end user 10 for manual activity as related to the use of tools orhand held devices. In the accompanying figures, welding, and morespecifically, arc welding is illustrated as performed by the end user 10on a weldment 15 (e.g., a weld coupon). The welding activity is recordedby the system 100 in real time or near-real time for tracking andanalysis purposes mentioned above by a real time tracking module 121 andan analysis module 122, respectively (see FIG. 4). By recorded it ismeant that the system 10 captures data related to a particular weldingprocess for determining the quality of the weld joint or weld joints.The types of performance data that may be captured include, but are notlimited to, for example: weld joint configuration or weld jointtrajectory, weld speed, welding torch pitch and roll angles, electrodedistance to the center weld joint, wire feed speed, electrodetrajectory, weld time, and time and date data. Other types of data mayalso be captured and/or entered into the system 100 including: weldmentmaterials, electrode materials, user name, project ID number, and thelike. Still, any type and quantity of information may be captured and/orentered into the system 100 as is suitable for tracking, analyzing andmanaging weld performance data. In this manner, detailed informationabout how the welding process for a particular weld joint was performedmay be captured and reconstructed for review and analysis in an analysisrecord 124.

The data captured and entered into the system 100 is used to determinethe quality of the real world weld joint. Persons of ordinary skill inthe art will understand that a weld joint may be analyzed by variousprocesses including destructive and non-destructive methods, examples ofwhich include sawing/cutting or x-raying of the weld joint respectively.In prior art methods such as these, trained or experienced weldpersonnel can determine the quality of a weld performed on a weld joint.Of course, destructive testing renders the weldment unusable and thuscan only be used for a sampling or a subset of welded parts. Whilenon-destructive testing, like x-raying, do not destroy the weldedarticle, these methods can be cumbersome to use and the equipmentexpensive to purchase. Moreover, some weld joints cannot beappropriately x-rayed, i.e. completely or thoroughly x-rayed. By way ofcontrast, system 100 captures performance data during the weldingprocess that can be used to determine the quality of the welded joint.More specifically, system 100 is used to identify potentialdiscontinuities and flaws within specific regions of a weld joint. Thecaptured data may be analyzed by an experienced welder or trainedprofessional (e.g., a trainer 123, see FIG. 4), or in an alternative bythe system 100 using the analysis module 122 for identifying areaswithin the weld joint that may be flawed. In one example, torch positionand orientation along with travel speed and other critical parametersare analyzed as a whole to predict which areas along the weld joint, ifany, are deficient. It will be understood that quality is achievedduring the welding process when the operator 10 keeps the weld torch 230within acceptable operational ranges. Accordingly, the performance datamay be analyzed against known good parameters for achieving weld qualityfor a particular weld joint configuration.

FIG. 6 illustrates an example embodiment of a graph 600, displayed onthe display 130, showing tracked welding tool pitch angle 640 versustime with respect to an upper pitch angle limit 610, a lower pitch anglelimit 620, and an ideal pitch angle 630. The upper and lower limits 610and 620 define a range of acceptability between them. Different limitsmay be predefined for different types of users such as, for example,welding novices, welding experts, and persons at a trade show. Theanalysis engine 122 may provide a scoring capability, in accordance withan embodiment of the present invention, where a numeric score isprovided based on how close to optimum (ideal) a user is for aparticular tracked parameter, and depending on the determined level ofdiscontinuities or defects determined to be present in the weld.

Performance data may be stored electronically in a database 140 (seeFIG. 3) and managed by a database manager in a manner suitable forindexing and retrieving selected sets or subsets of data. In oneembodiment, the data is retrieved and presented to an analyzing user(e.g., a trainer 123) for determining the weld quality of a particularweld joint. The data may be presented in tabular form for analysis bythe analyzing user. Pictures, graphs, and or other symbol data may alsobe presented as is helpful to the analyzing user in determining weldquality. In an alternative embodiment, the performance data may bepresented to the analyzing user in a virtual reality setting, wherebythe real world welding process is simulated using real world data ascaptured by the system 100. An example of such a virtual reality settingis discussed in U.S. patent application Ser. No. 12/501,257 filed onJul. 10, 2009. In this way, the weld joint and corresponding weldingprocess may be reconstructed for review and analysis. Accordingly, thesystem 100 may be used to archive real data as it relates to aparticular welded article. Still, it will be construed that any mannerof representing captured data or reconstructing the welding process forthe analyzing user may be used as is appropriate for determining weldquality.

In another embodiment, data captured and stored in the database 140 isanalyzed by an analyzing module 122 (a.k.a., an analysis engine) of thesystem 100. The analyzing module 122 may comprise a computer programproduct executed by the processor based computing device 110. Thecomputer program product may use artificial intelligence. In oneparticular embodiment, an expert system may be programmed with dataderived from a knowledge expert and stored within an inference enginefor independently analyzing and identifying flaws within the weld joint.By independently, it is meant that the analyzing module 122 functionsindependently from the analyzing user to determine weld quality. Theexpert system may be ruled-based and/or may incorporate fuzzy logic toanalyze the weld joint. In this manner, areas along the weld joint maybe identified as defective, or potentially defective, and marked forsubsequent review by an analyzing user. Determining weld quality and/orproblem areas within the weld joint may be accomplished by heuristicmethods. As the system 100 analyzes welding processes of the various endusers over repeated analyzing cycles, additional knowledge may be gainedby the system 100 for determining weld quality.

A neural network or networks may be incorporated into the analysisengine 122 of the system 100 for analyzing data to determine weldquality, weld efficiency and/or weld flaws or problems. Neural networksmay comprise software programming that simulates decision makingcapabilities. In one embodiment, the neural network(s) may process datacaptured by the system 100 making decisions based on weighted factors.It is noted that the neural network(s) may be trained to recognizeproblems that may arise from the weld torch position and movement, aswell as other critical welding factors. Therefore, as data from thewelding process is captured and stored, the system 100 may analyze thedata for identifying the quality of the weld joint. Additionally, thesystem 100 may provide an output device 170 (see FIG. 4) that outputsindications of potential flaws in the weld such as, for example,porosity, weld overfill, and the like.

In capturing performance data, the system 100 incorporates a series ofsensors, also referred to as sensor arrays 160, 165 (see FIG. 2). Thesensor arrays 160, 165 include emitters and receivers positioned atvarious locations in proximity to the weldment 15, and morespecifically, in proximity to the weld joint 16 for determining theposition and orientation of the weld torch 230 in real time (or nearreal time). In one embodiment, the sensor arrays 160, 165 includeacoustical sensor elements. It is noted that the acoustical sensorelements may use waves in the sub-sonic and/or ultra-sonic range.Alternate embodiments are contemplated that use optical sensor elements,infrared sensor elements, laser sensor elements, magnetic sensorelements, or electromagnetic (radio frequency) sensor elements. In thismanner, the sensor emitter elements emit waves of energy in any ofvarious forms that are picked up by the sensor receiver elements. Tocompensate for noise introduced by the welding process, the system 100may also include bandwidth suppressors, which may be implemented in theform of software and/or electronic circuitry. The bandwidth suppressorsare used to condition the sensor signals to penetrate interferencecaused by the welding arc. Additionally, the system 100 may furtherincorporate inertial sensors, which may include one or moreaccelerometers. In this manner, data relating to position, orientation,velocity, and acceleration may be required to ascertain the movements(i.e., motion) of the weld torch 230.

In one embodiment, part of the sensor arrays 160, 165 are received bythe weld torch 230. That is to say that a portion of the sensors orsensor elements are affixed with respect to the body of the weld torch230 (see sensor array 160 165 of FIG. 2). In other embodiments, sensorsand/or sensor elements may be affixed to a portion of the article beingwelded (see sensor array 165 160 of FIG. 2). Still any manner ofpositioning and connecting the sensor elements may be chosen as isappropriate for tracking welding activity.

As an example of sensing and tracking a welding tool 230, in accordancewith an embodiment of the present invention, a magnetic sensingcapability may be provided. For example, the receiver sensor array 165may be a magnetic sensor that is mounted on the welding tool 230, andthe emitter sensor array 160 may take the form of a magnetic source. Themagnetic source 160 may be mounted in a predefined fixed position andorientation with respect to the weldment 15. The magnetic source 160creates a magnetic field around itself, including the space encompassingthe welding tool 230 during use and establishes a 3D spatial frame ofreference. The magnetic sensor 165 is provided which is capable ofsensing the magnetic field produced by the magnetic source. The magneticsensor 165 is attached to the welding tool 230 and is operativelyconnected to the processor based computing device 110 via, for example,a cable, or wirelessly. The magnetic sensor 165 includes an array ofthree induction coils orthogonally aligned along three spatialdirections. The induction coils of the magnetic sensor 165 each measurethe strength of the magnetic field in each of the three directions andprovide that information to the real time tracking module 121 of theprocessor based computing device 110. As a result, the system 100 isable to know where the welding tool 230 is in space with respect to the3D spatial frame of reference established by the magnetic field producedby the magnetic source 160. In accordance with other embodiments of thepresent invention, two or more magnetic sensors may be mounted on orwithin the welding tool 230 to provide a more accurate representation ofthe position and orientation of the welding tool 230, for example. Careis to be taken in establishing the magnetic 3D spatial frame ofreference such that the weldment 15, the tool 230, and any otherportions of the welding environment do not substantially distort themagnetic field created by the magnetic source 160. As an alternative,such distortions may be corrected for or calibrated out as part of awelding environment set up procedure. Other non-magnetic technologies(e.g., acoustic, optical, electromagnetic, inertial, etc.) may be used,as previously discussed herein, to avoid such distortions, as are wellknown in the art.

With reference to all of the figures, operation of the system 100 willnow be described in accordance with an embodiment of the presentinvention. The end user 10 activates the system 100 and enters his orher user name via the user interface 135. Once authorized access hasbeen gained, the end user 10 traverses the menu system as prompted bythe computer program product 120 via the GUI 135. The system 100instructs the end user 10 to initiate set up of the welding article 15,which includes entering information about the weldment materials and/orwelding process being used. Entering such information may include, forexample, selecting a language, entering a user name, selecting a weldcoupon type, selecting a welding process and associated axial spray,pulse, or short arc methods, selecting a gas type and flow rate,selecting a type of stick electrode, and selecting a type of flux coredwire.

In one embodiment, the end user enters the starting and ending points ofthe weld joint 16. This allows the system 100, via the real timetracking module 121, to determine when to start and stop recording thetracked information. Intermediate points are subsequently entered forinterpolating the weld joint trajectory as calculated by the system 100.Additionally, sensor emitters and/or receivers 160, 165 are placedproximate to the weld joint at locations suitable for gathering data ina manner consistent with that described herein. After set up iscompleted, system tracking is initiated and the end user 10 is promptedto begin the welding procedure. As the end user 10 completes the weld,the system 100 gathers performance data including the speed, positionand orientation of the weld torch 230 for analysis by the system 100 indetermining welder performance characteristics and weld qualitycharacteristics as previously described herein.

In summary, a system and a method for tracking and analyzing weldingactivity is disclosed. Dynamic spatial properties of a welding tool aresensed during a welding process producing a weld. The sensed dynamicspatial properties are tracked over time and the tracked dynamic spatialproperties are captured as tracked data during the welding process. Thetracked data is analyzed to determine performance characteristics of awelder performing the welding process and quality characteristics of aweld produced by the welding process. The performance characteristicsand the quality characteristics may be subsequently reviewed.

While the claimed subject matter of the present application has beendescribed with reference to certain embodiments, it will be understoodby those skilled in the art that various changes may be made andequivalents may be substituted without departing from the scope of theclaimed subject matter. In addition, many modifications may be made toadapt a particular situation or material to the teachings of the claimedsubject matter without departing from its scope. Therefore, it isintended that the claimed subject matter not be limited to theparticular embodiment disclosed, but that the claimed subject matterwill include all embodiments falling within the scope of the appendedclaims.

What is claimed is:
 1. A system for tracking and analyzing weldingactivity, said system comprising: means for automatically sensingdynamic spatial properties of a welding tool during a welding processproducing a real world weld; means for automatically tracking saidsensed dynamic spatial properties over time during said welding process;means for automatically capturing in real time or near real time saidtracked dynamic spatial properties as tracked data during said weldingprocess; and means for automatically analyzing in real time or near realtime said tracked data to determine at least one of performancecharacteristics of a welder performing said welding process and aquality characteristics characteristic of a said real world weldproduced by said welding process.
 2. The system of claim 1, wherein saidanalyzing further comprises determining a performance characteristic ofa welder performing said welding process, and said system furthercomprising comprises means for reviewing said performancecharacteristics characteristic of a said welder performing said weldingprocess.
 3. The system of claim 1 further comprising means for reviewingsaid quality characteristics characteristic of a said real world weldproduced by said welding process.
 4. The system of claim 1 furthercomprising means for a user to locally interact with said system.
 5. Thesystem of claim 1 further comprising means for a user to remotelyinteract with said system.
 6. The system of claim 1 further comprisingmeans for automatically authorizing access to a user of said system. 7.The system of claim 1, wherein said analyzing comprises determining aperformance characteristic of a welder performing said welding process,and wherein said performance characteristics of a welder includecharacteristic includes at least one of a weld joint trajectory, atravel speed of said welding tool, welding tool pitch and roll angles,an electrode distance to a center weld joint, an electrode trajectory,and a weld time.
 8. The system of claim 1 wherein said qualitycharacteristics of a weld produced by said welding process includecharacteristic includes at least one of discontinuities and flaws withinregions of a said real world weld produced by said welding process.
 9. Asystem for tracking and analyzing welding activity, said systemcomprising: at least one sensor array configured to sense dynamicspatial properties of a welding tool during a welding process producinga real world weld; a processor based computing device operativelyinterfacing to said at least one sensor array and configured to trackand analyze in real time or near real time said dynamic spatialproperties of a said welding tool over time during a said weldingprocess producing a said real world weld; and at least one userinterface operatively interfacing to said processor based computingdevice, said at least one user interface displaying a qualitycharacteristic of said real world weld produced by said welding process.10. The system of claim 9 wherein said at least one user interfaceincludes a graphical user interface.
 11. The system of claim 9 whereinsaid at least one user interface includes a display device.
 12. Thesystem of claim 9 further comprising a network interface configured tointerface said processor based computing device to an externalcommunication network.
 13. The system of claim 9 wherein said at leastone sensor array includes at least one of acoustical sensor elements,optical sensor elements, magnetic sensor elements, inertial sensorelements, and electromagnetic sensor elements.
 14. A method for trackingand analyzing welding activity, said method comprising: sensing dynamicspatial properties of a welding tool during a welding process producinga real world weld using at least one sensor; tracking said senseddynamic spatial properties over time in real time or near real timeduring said welding process using a real time tracking module; capturingsaid tracked dynamic spatial properties as tracked data in real time ornear real time during said welding process using a computer based memorydevice; and analyzing said tracked data in real time or near real timeto determine at least one of performance characteristics of a welderperforming said welding process and a quality characteristicscharacteristic of a said real world weld produced by said weldingprocess using a computer based analysis engine.
 15. The method of claim14, wherein said analyzing further comprises determining a performancecharacteristic of a welder performing said welding process, and whereinsaid method further comprising comprises outputting said performancecharacteristics characteristic of a said welder performing said weldingprocess to at least one of a display device, a visualization module, anda testing module for review.
 16. The method of claim 14 furthercomprising outputting said quality characteristics characteristic of asaid real world weld produced by said welding process to at least one ofa display device, a visualization module, and a testing module forreview.
 17. The method of claim 14 further comprising selecting weldingset up parameters for said welding process via a user interface.
 18. Themethod of claim 14 15 further comprising remotely reviewing at least oneof said performance characteristics characteristic of a said welderperforming said welding process and said quality characteristicscharacteristic of a said real world weld produced by said weldingprocess, via a communication network.
 19. The method of claim 14,wherein said analyzing further comprises determining a performancecharacteristic of a welder performing said welding process, and whereinsaid performance characteristics of a welder include characteristicincludes at least one of a weld joint trajectory, a travel speed of saidwelding tool, welding tool pitch and roll angles, an electrode distanceto a center weld joint, an electrode trajectory, and a weld time. 20.The method of claim 14 wherein said quality characteristics of a weldproduced by said welding process include characteristic includes atleast one of discontinuities and flaws within regions of a said realworld weld produced by said welding process.
 21. The system of claim 9,wherein said analysis of said spatial properties comprise determining atleast one of a performance characteristic of a welder performing saidwelding process and a quality characteristic of said real world weld.22. The system of claim 21, wherein said performance characteristicincludes at least one of a weld joint trajectory, a travel speed of saidwelding tool, welding tool pitch and roll angles, an electrode distanceto a center weld joint, an electrode trajectory, and a weld time. 23.The system of claim 21, wherein said quality characteristic includes atleast one of a discontinuity and a flaw within a region of said weldproduced by said welding process.
 24. The system of claim 23, whereinsaid quality characteristic includes said flaw and said flaw comprisesat least one of porosity and weld overfill.
 25. The system of claim 24,wherein said spatial properties comprise at least one of a position, anorientation, and a movement of said welding tool.
 26. The system ofclaim 9, wherein said welding tool comprises a portion of said at leastone sensor array.
 27. The system of claim 26, wherein said portion ofsaid at least one sensor array includes at least one of acousticalsensor elements, magnetic sensor elements, inertial sensor elements, andelectromagnetic sensor elements.
 28. The system of claim 12, whereinsaid network interface is configured to transmit data representing saidwelding process to a remote system.
 29. The system of claim 28, whereinsaid transmitted data comprises information related to a welder'sperformance.
 30. The system of claim 9, wherein said processor basedcomputing device is further configured to record in real time or nearreal time performance data corresponding to said welding process, andwherein said performance data comprises at least one of a weld jointconfiguration or a weld joint trajectory, a weld speed, welding toolpitch and roll angles, an electrode distance to a center weld joint, awire feed speed, an electrode trajectory, a weld time, and time and datedata.
 31. The system of claim 30, wherein said processor based computingdevice is further configured to record at least one of weldmentmaterials, electrode materials, user name, and project ID number. 32.The system of claim 31, wherein said analyzing further comprisescomparing said performance data to known parameters to determine saidquality characteristic of said real world weld.
 33. The system of claim9, wherein said analyzing comprises determining a score based on acomparison of at least one of said tracked spatial properties to anoptimum value corresponding to said at least one of said tracked spatialproperties.
 34. The system of claim 33, wherein said optimum value is arange comprising an upper limit and a lower limit for said at least oneof said tracked spatial properties.
 35. The system of claim 34, whereinsaid tracked spatial properties comprise at least one of a weld jointtrajectory, a weld speed, welding tool pitch angle, welding tool rollangle, an electrode distance to a center weld joint, a wire feed speed,and an electrode trajectory.
 36. The system of claim 35, wherein saidtracked spatial properties includes said welding tool pitch angle. 37.The system of claim 9, wherein said welding process is performedmanually.
 38. The system of claim 9, wherein said welding process isperformed by a robotic welder.
 39. The system of claim 11, wherein saiddisplay device is integrated into a welding helmet.
 40. The system ofclaim 9, wherein said processor based computing device is configured toset up a virtual reality setting in which said welding process can besimulated using said spatial properties of said welding tool.
 41. Thesystem of claim 9, wherein said welding tool is one of an electrodeholder and a welding torch.
 42. The system of claim 9, wherein saidanalysis is performed by an expert system configured identify defectiveor potentially defective areas along a weld joint.
 43. The system ofclaim 42, wherein said expert system comprises at least one of arule-based system and a neural network.
 44. The system of claim 43,wherein said expert system is said neural network and said analysis isbased on weighted factors.
 45. The system of claim 9, wherein saidprocessor based computing device is further configured to captureinformation corresponding to said welding process in an analysis recordfor subsequent review.
 46. The method of claim 14, wherein said sensingcomprises measuring at least one of an acoustical signal, a magneticsignal, an optical signal, inertial signal, and an electromagneticsignal.
 47. The method of claim 14, further comprising transmitting to aremote system data representing said welding process.
 48. The method ofclaim 47, further comprising analyzing said welding process based onsaid transmitted data.
 49. The method of claim 14, further comprisingrecording in real time or near real time performance data correspondingto said welding process, wherein said performance data comprises atleast one of a weld joint configuration or a weld joint trajectory, aweld speed, welding tool pitch and roll angles, an electrode distance toa center weld joint, a wire feed speed, an electrode trajectory, a weldtime, and time and date data.
 50. The method of claim 49, wherein saidrecording further comprises recording data corresponding to at least oneof weldment materials, electrode materials, user name, and project IDnumber.
 51. The method of claim 49, wherein said analyzing comprisescomparing said performance data to known parameters to determine saidquality characteristic of said real world weld.
 52. The method of claim14, wherein said analyzing comprises determining a score based on acomparison of at least one of said tracked spatial properties to anoptimum value.
 53. The method of claim 52, wherein said optimum value isa range comprising an upper limit and a lower limit for said at leastone of said tracked spatial properties.
 54. The method of claim 53,wherein said tracked spatial properties comprise at least one of a weldjoint trajectory, a weld speed, welding tool pitch angle, welding toolroll angle, an electrode distance to a center weld joint, a wire feedspeed, and an electrode trajectory.
 55. The system of claim 54, whereinsaid tracked spatial properties includes said welding tool pitch angle.56. The method of claim 14, wherein said welding process is performedmanually.
 57. The method of claim 14, wherein said welding process isperformed by a robotic welder.
 58. The method of claim 14, furthercomprising storing information on said welding process an analysisrecord.
 59. The method of claim 15, wherein said display device isintegrated into a welding helmet.
 60. The method of claim 16, whereinsaid display device is integrated into a welding helmet.
 61. The methodof claim 14, further comprising setting up a virtual reality setting inwhich said welding process can be simulated using said spatialproperties of said welding tool.
 62. The method of claim 14, whereinsaid welding tool is one of an electrode holder and a welding torch. 63.The method of claim 14, further comprising using an expert system toidentify defective or potentially defective areas along said weld. 64.The method of claim 63, wherein said expert system uses at least one ofa rule-based system and a neural network.
 65. The method of claim 64,wherein said expert system uses said neural network and saididentification is based on weighted factors.
 66. The method of claim 14,further comprising capturing information corresponding to said weldingprocess in an analysis record for subsequent review.
 67. The method ofclaim 20, wherein said flaws comprise at least one of porosity and weldoverfill.
 68. The method of claim 67, wherein said spatial propertiescomprise at least one of a position, an orientation, and a movement ofsaid welding tool.
 69. A system for tracking and analyzing weldingactivity, said system comprising: at least one sensor array configuredto sense spatial properties of a welding tool during a welding processproducing a real world weld; and a processor based computing deviceoperatively interfacing to said at least one sensor array and configuredto track said spatial properties and record performance datacorresponding to said welding process, said processor based computingdevice further configured to determine a quality characteristic of saidreal world weld.
 70. The system of claim 69, wherein said analysiscomprises comparing said performance data to known parameters todetermine said quality characteristic of said weld.
 71. The system ofclaim 70, wherein said quality characteristic includes at least one of adiscontinuity and a flaw within a region of said weld.
 72. The system ofclaim 71, wherein said recording is performed in real time or near realtime.
 73. The system of claim 72, wherein said spatial propertiescomprise at least one of a position, an orientation, and a movement ofsaid welding tool, and wherein said performance data comprises at leastone of a weld joint configuration or a weld joint trajectory, a weldspeed, welding tool pitch and roll angles, an electrode distance to acenter weld joint, a wire feed speed, an electrode trajectory, a weldtime, and time and date data.
 74. The system of claim 73, wherein saidprocessor based computing device is further configured to record atleast one of weldment materials, electrode materials, user name, andproject ID number.
 75. The system of claim 73, wherein said analyzingfurther comprises determining a score based on at least a comparison ofat least one of said tracked spatial properties to an optimum value saidat least one of said tracked spatial properties.
 76. The system of claim75, wherein said optimum value is a range comprising an upper limit anda lower limit for said at least one of said tracked spatial properties.77. The system of claim 76, wherein said tracked spatial propertiescomprise at least one of a weld joint trajectory, a weld speed, weldingtool pitch angle, welding tool roll angle, an electrode distance to acenter weld joint, a wire feed speed, and an electrode trajectory. 78.The system of claim 77, wherein said tracked spatial properties includessaid welding tool pitch angle.
 79. The system of claim 71, wherein saidquality characteristic includes said flaw and said flaw comprises atleast one of porosity and weld overfill.
 80. The system of claim 69,wherein said welding process is performed manually.
 81. The system ofclaim 69, wherein said welding process is performed by a robotic welder.82. The system of claim 69, further comprising a display device todisplay said quality characteristic.
 83. The system of claim 82, whereinsaid display device is integrated into a welding helmet.
 84. The systemof claim 69, wherein said processor based computing device is configuredto set up a virtual reality setting in which said welding process can besimulated using said spatial properties of said welding tool.
 85. Thesystem of claim 69, wherein said welding tool is one of an electrodeholder and a welding torch.
 86. The system of claim 69, wherein saidanalysis is performed by an expert system configured identify defectiveor potentially defective areas along said weld.
 87. The system of claim86, wherein said expert system is a neural network and said analysis isbased on weighted factors.
 88. The system of claim 69, wherein saidprocessor based computing device is further configured to captureinformation corresponding to said welding process in an analysis recordfor subsequent review.
 89. A system for tracking and analyzing weldingactivity, said system comprising: a tracking module configured to trackspatial positions of a welding tool during a welding process; and aprocessor subsystem configured to ascertain at least one weldingparameter during the welding process based on said tracked spatialpositions and to determine a score based on a comparison of said atleast one welding parameter to an optimum value.
 90. The system of claim89, wherein said at least one welding parameter includes a performancecharacteristic of a welder.
 91. The system of claim 89, wherein said atleast one welding parameter includes a quality characteristic of a weld.92. The system of claim 89, wherein said at least one welding parameterincludes a performance characteristic of a welder and a qualitycharacteristic of a weld.
 93. The system of claim 89, wherein saidprocessor subsystem includes an expert system.
 94. The system of claim93, wherein said expert system comprises at least one of a rule-basedsystem and a neural network.
 95. The system of claim 89, wherein saidoptimum value is a range comprising an upper limit and a lower limit forsaid at least one welding parameter.
 96. The system of claim 95, whereinsaid at least one welding parameter comprises at least one of a weldjoint trajectory, a weld speed, welding tool pitch angle, welding toolroll angle, an electrode distance to a center weld joint, a wire feedspeed, and an electrode trajectory.
 97. The system of claim 96, whereinsaid tracked spatial properties includes said welding tool pitch angle.98. The system of claim 97, wherein said welding process is performedmanually.
 99. The system of claim 89, wherein said welding process isperformed by a robotic welder.
 100. The system of claim 91, furthercomprising a display device to display said quality characteristic. 101.The system of claim 100, wherein said display is integrated into awelding helmet.
 102. The system of claim 89, wherein said processorbased computing device is configured to set up a virtual reality settingin which said welding process can be simulated using said spatialproperties of said welding tool.
 103. The system of claim 89, whereinsaid welding tool is one of an electrode holder and a welding torch.104. A method for tracking and analyzing welding activity, said methodcomprising: sensing spatial properties of a welding tool during awelding process producing a real world weld; tracking said sensedspatial properties; recording performance data corresponding to saidwelding process; and analyzing said performance data in real-time ornear real-time to determine a quality characteristic of said real worldweld produced by said welding process.
 105. The method of claim 104,wherein said analyzing comprises comparing said performance data to aknown parameter to determine said quality characteristic of said realworld weld.
 106. The method of claim 105, wherein said welding processis performed by a robotic welder.
 107. The method of claim 105, whereinsaid quality characteristic includes at least one of a discontinuity anda flaw within a region of said real world weld.
 108. The method of claim107, wherein said quality characteristic includes said flaw and saidflaw comprises at least one of porosity and weld overfill.
 109. Themethod of claim 107, wherein said recording is performed in real time ornear real time.
 110. The method of claim 109, wherein said spatialproperties comprise at least one of a position, an orientation, and amovement of said welding tool, and wherein said performance datacomprises at least one of a weld joint configuration or a weld jointtrajectory, a weld speed, welding tool pitch and roll angles, anelectrode distance to a center weld joint, a wire feed speed, anelectrode trajectory, a weld time, and time and date data.
 111. Themethod of claim 110, wherein further comprising recording at least oneof weldment materials, electrode materials, user name, and project IDnumber.
 112. The method of claim 104, wherein said analyzing furthercomprises determining a score based on at least a comparison of at leastone of said tracked spatial properties to an optimum value.
 113. Themethod of claim 112, wherein said optimum value is a range comprising anupper limit and a lower limit for said at least one of said trackedspatial properties.
 114. The method of claim 113, wherein said trackedspatial properties comprise at least one of a weld joint trajectory, aweld speed, welding tool pitch angle, welding tool roll angle, anelectrode distance to a center weld joint, a wire feed speed, and anelectrode trajectory.
 115. The system of claim 114, wherein said trackedspatial properties includes said welding tool pitch angle.
 116. Themethod of claim 104, wherein said welding process is performed manually.117. The method of claim 104, further comprising outputting said qualitycharacteristic to a display device.
 118. The method of claim 117,wherein said display device is integrated into a welding helmet. 119.The method of claim 104, further comprising setting up a virtual realitysetting in which said welding process can be simulated using saidspatial properties of said welding tool.
 120. The method of claim 104,wherein said welding tool is one of an electrode holder and a weldingtorch.
 121. The method of claim 104, further comprising using an expertsystem to identify defective or potentially defective areas along saidweld.
 122. The method of claim 121, wherein said expert system is aneural network and said identification is based on weighted factors.123. The method of claim 104, further comprising capturing informationcorresponding to said welding process in an analysis record forsubsequent review.
 124. A method for tracking and analyzing weldingactivity, said system comprising: tracking spatial positions of awelding tool during a welding process; determining at least one weldingparameter during the welding process based on said tracked spatialpositions; determining a score based on a comparison of said at leastone welding parameter to an optimum value.
 125. The method of claim 124,wherein said determining of said at least one welding parametercomprises analyzing a performance characteristic of a welder.
 126. Themethod of claim 124, wherein said determining of said at least onewelding parameter comprises analyzing a quality characteristic of aweld.
 127. The method of claim 124, wherein said determining of said atleast one welding parameter comprises analyzing a performancecharacteristic of a welder and a quality characteristic of a weld. 128.The method of claim 124, wherein said determining of said at least onewelding parameter comprises using an expert system.
 129. The method ofclaim 128, wherein said expert system uses at least one of a rule-basedsystem and a neural network.
 130. The method of claim 124, wherein saidoptimum value is a range comprising an upper limit and a lower limit forsaid at least one welding parameter.
 131. The method of claim 130,wherein said at least one welding parameter comprises at least one of aweld joint trajectory, a weld speed, welding tool pitch angle, weldingtool roll angle, an electrode distance to a center weld joint, a wirefeed speed, and an electrode trajectory.
 132. The method of claim 131,wherein said at least one welding parameter includes said welding toolpitch angle.
 133. The method of claim 124, wherein said welding processis performed manually.
 134. The method of claim 124, wherein saidwelding process is performed by a robotic welder.
 135. The method ofclaim 124, further comprising setting up a virtual reality setting inwhich said welding process can be simulated using said spatialproperties of said welding tool.
 136. The system of claim 124, whereinsaid welding tool is one of an electrode holder and a welding torch.137. A system for tracking welding activity, said system comprising: anoptical tracking system that tracks at least one of a position, amovement, and an orientation of a welding tool; and a computeroperatively interfacing to said optical tracking system, said computerdetermining at least one parameter that is at least one of a travelspeed, a pitch angle, a roll angle, and an electrode distance to acenter weld joint of said welding tool, wherein said processor basedcomputing device determines for each of said at least one parameter ascore based on a comparison of said parameter to at least onepredetermined limit for said parameter.
 138. The system of claim 137,wherein said score relates to a weld quality of a real world weld. 139.The system of claim 138, wherein said score relates to said weld qualityof said real world weld, and wherein said weld quality includes anindication of at least one of a discontinuity and a flaw within a regionof said real world weld.
 140. The system of claim 139, wherein said weldquality includes an indication of said flaw and said flaw comprises atleast one of porosity and weld overfill.
 141. The system of claim 139,wherein said determination of said score is performed in real time ornear real time.
 142. The system of claim 138, wherein an expert systemidentifies defective or potentially defective areas along said realworld weld.
 143. The system of claim 137, wherein said at least oneparameter further includes at least one of a weld joint configuration ora weld joint trajectory, a weld speed, a wire feed speed, an electrodetrajectory, a weld time, and time and date data.
 144. The system ofclaim 137, wherein said processor based computing device is furtherconfigured to record at least one of weldment materials, electrodematerials, user name, and project ID number.
 145. The system of claim137, wherein said at least one predetermined limit includes an upperlimit and a lower limit.
 146. The system of claim 137, furthercomprising a display device to display said score.
 147. The system ofclaim 146, wherein said display device is integrated into a weldinghelmet.
 148. The system of claim 137, wherein said welding tool is oneof an electrode holder and a welding torch.
 149. A system for trackingwelding activity, said system comprising: an infrared tracking systemthat tracks at least one of a position, a movement, and an orientationof a welding tool based on an infrared element attached to said weldingtool; and a computer operatively interfacing to said infrared trackingsystem, said computer determining at least one parameter that is atleast one of a travel speed, a pitch angle, a roll angle, and anelectrode distance to a center weld joint of said welding tool, whereinsaid computer determines for each of said at least one parameter a scorebased on a comparison of said parameter to at least one predeterminedlimit for said parameter.
 150. The system of claim 149, wherein saidscore relates to a weld quality of a real world weld.
 151. The system ofclaim 150, wherein an expert system identifies defective or potentiallydefective areas along said real world weld.
 152. The system of claim150, wherein said score relates to said weld quality of said real worldweld, and wherein said weld quality includes an indication of at leastone of a discontinuity and a flaw within a region of said real worldweld.
 153. The system of claim 152, wherein said weld quality includesan indication of said flaw and said flaw comprises at least one ofporosity and weld overfill.
 154. The system of claim 152, wherein saiddetermination of said score is performed in real time or near real time.155. The system of claim 149, wherein said at least one parameterfurther includes at least one of a weld joint configuration or a weldjoint trajectory, a weld speed, a wire feed speed, an electrodetrajectory, a weld time, and time and date data.
 156. The system ofclaim 149, wherein said processor based computing device is furtherconfigured to record at least one of weldment materials, electrodematerials, user name, and project ID number.
 157. The system of claim149, wherein said at least one predetermined limit includes an upperlimit and a lower limit.
 158. The system of claim 149, furthercomprising a display device to display said score.
 159. The system ofclaim 158, wherein said display device is integrated into a weldinghelmet.
 160. The system of claim 149, wherein said welding tool is oneof an electrode holder and a welding torch.
 161. A method for trackingwelding activity, said method comprising: optically tracking at leastone of a position, a movement, and an orientation of a welding tool;determining at least one parameter that is at least one of a travelspeed, a pitch angle, a roll angle, and an electrode distance to acenter weld joint of said welding tool; and computing for each of saidat least one parameter a score based on a comparison of said parameterto at least one predetermined limit for said parameter.
 162. The methodof claim 161, wherein said score relates to a weld quality of a realworld weld.
 163. The method of claim 162, wherein an expert systemidentifies defective or potentially defective areas along said realworld weld.
 164. The method of claim 162, wherein said score relates tosaid weld quality of said real world weld, and wherein said weld qualityincludes an indication of at least one of a discontinuity and a flawwithin a region of said real world weld.
 165. The method of claim 164,wherein said weld quality includes an indication of said flaw and saidflaw comprises at least one of porosity and weld overfill.
 166. Themethod of claim 164, wherein said determination of said score isperformed in real time or near real time.
 167. The method of claim 161,wherein said at least one parameter further includes at least one of aweld joint configuration or a weld joint trajectory, a weld speed, awire feed speed, an electrode trajectory, a weld time, and time and datedata.
 168. The method of claim 167, wherein said processor basedcomputing device is further configured to record at least one ofweldment materials, electrode materials, user name, and project IDnumber.
 169. The method of claim 161, wherein said at least onepredetermined limit includes an upper limit and a lower limit.
 170. Themethod of claim 161, further comprising a display device to display saidscore.
 171. The method of claim 170, wherein said display device isintegrated into a welding helmet.
 172. The method of claim 161, whereinsaid welding tool is one of an electrode holder and a welding torch.173. A method for tracking welding activity, said method comprising:tracking by infrared at least one of a position, a movement, and anorientation of a welding tool based on an infrared element attached tosaid welding tool; determining at least one parameter that is at leastone of a travel speed, a pitch angle, a roll angle, and an electrodedistance to a center weld joint of said welding tool; and computing foreach of said at least one parameter a score based on a comparison ofsaid parameter to at least one predetermined limit for said parameter.174. The method of claim 173, wherein said score relates to a weldquality of a real world weld.
 175. The method of claim 174, wherein saidscore relates to said weld quality of said real world weld, and whereinsaid weld quality includes an indication of at least one of adiscontinuity and a flaw within a region of said real world weld. 176.The method of claim 175, wherein said weld quality includes anindication of said flaw and said flaw comprises at least one of porosityand weld overfill.
 177. The method of claim 175, wherein saiddetermination of said score is performed in real time or near real time.178. The method of claim 174, wherein an expert system identifiesdefective or potentially defective areas along said real world weld.179. The method of claim 173, wherein said at least one parameterfurther includes at least one of a weld joint configuration or a weldjoint trajectory, a weld speed, a wire feed speed, an electrodetrajectory, a weld time, and time and date data.
 180. The method ofclaim 179, wherein said processor based computing device is furtherconfigured to record at least one of weldment materials, electrodematerials, user name, and project ID number.
 181. The method of claim173, wherein said at least one predetermined limit includes an upperlimit and a lower limit.
 182. The method of claim 173, furthercomprising a display device to display said score.
 183. The method ofclaim 182, wherein said display device is integrated into a weldinghelmet.
 184. The method of claim 173, wherein said welding tool is oneof an electrode holder and a welding torch.
 185. A system for trackingand analyzing welding activity, said system comprising: at least onesensor array configured to sense spatial properties of a welding toolduring a welding process producing a real world weld; a processor basedcomputing device operatively interfacing to said at least one sensorarray and configured to track and analyze in real time or near real timesaid spatial properties of said welding tool during said welding processproducing said real world weld; and at least one display interfacing tosaid processor based computing device, said at least one displaydisplaying a quality characteristic of said real world weld produced bysaid welding process.
 186. A system for tracking welding activity, saidsystem comprising: an infrared tracking system that tracks at least oneof a position, a movement, and an orientation of a welding tool based onan infrared emitter attached to said welding tool; and a computeroperatively interfacing to said infrared tracking system, said computerdetermining at least one parameter that is at least one of a travelspeed, a pitch angle, a roll angle, and an electrode distance to acenter weld joint of said welding tool, wherein said computer determinesfor each of said at least one parameter a score based on a comparison ofsaid parameter to at least one predetermined limit for said parameter.187. A method for tracking welding activity, said method comprising:tracking by infrared at least one of a position, a movement, and anorientation of a welding tool based on an infrared emission from saidwelding tool; determining at least one parameter that is at least one ofa travel speed, a pitch angle, a roll angle, and an electrode distanceto a center weld joint of said welding tool, computing for each of saidat least one parameter a score based on a comparison of said parameterto at least one predetermined limit for said parameter.
 188. A systemfor tracking welding activity, said system comprising: an opticaltracking system that tracks in real time or near real time at least oneof a position, a movement, and an orientation of a welding tool; and acomputer operatively interfacing to said optical tracking system, saidcomputer determining in real time or near real time at least oneparameter that is at least one of a travel speed, a pitch angle, a rollangle, and an electrode distance to a center weld joint of said weldingtool, wherein said processor based computing device determines for eachof said at least one parameter a score based on a comparison of saidparameter to at least one predetermined limit for said parameter, andwherein said score relates to a weld quality of a real world weld. 189.The system of claim 188, wherein said determination of said score isperformed in real time or near real time.
 190. A system for trackingwelding activity, said system comprising: an infrared tracking systemthat tracks in real time or near real time at least one of a position, amovement, and an orientation of a welding tool based on an infraredelement attached to said welding tool; and a computer operativelyinterfacing to said infrared tracking system, said computer determiningin real time or near real time at least one parameter that is at leastone of a travel speed, a pitch angle, a roll angle, and an electrodedistance to a center weld joint of said welding tool, wherein saidcomputer determines for each of said at least one parameter a scorebased on a comparison of said parameter to at least one predeterminedlimit for said parameter, and wherein said score relates to a weldquality of a real world weld.
 191. The system of claim 190, wherein saiddetermination of said score is performed in real time or near real time.192. A method for tracking welding activity, said method comprising:optically tracking in real time or near real time at least one of aposition, a movement, and an orientation of a welding tool; determiningin real time or near real time at least one parameter that is at leastone of a travel speed, a pitch angle, a roll angle, and an electrodedistance to a center weld joint of said welding tool; and computing foreach of said at least one parameter a score based on a comparison ofsaid parameter to at least one predetermined limit for said parameter,and wherein said score relates to a weld quality of a real world weld.193. The method of claim 192, wherein said determination of said scoreis performed in real time or near real time.
 194. A method for trackingwelding activity, said method comprising: tracking by infrared in realtime or near real time at least one of a position, a movement, and anorientation of a welding tool based on an infrared element attached tosaid welding tool; determining in real time or near real time at leastone parameter that is at least one of a travel speed, a pitch angle, aroll angle, and an electrode distance to a center weld joint of saidwelding tool; and computing for each of said at least one parameter ascore based on a comparison of said parameter to at least onepredetermined limit for said parameter, and wherein said score relatesto a weld quality of a real world weld.
 195. The method of claim 194,wherein said determination of said score is performed in real time ornear real time.